Triple

T10689294
Position Surface form Disambiguated ID Type / Status
Subject Ebersberg E251965 entity
Predicate surroundedBy P224 FINISHED
Object Ebersberger Forst E879207 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ebersberger Forst | Statement: [Ebersberg, surroundedBy, Ebersberger Forst]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ebersberger Forst
Context triple: [Ebersberg, surroundedBy, Ebersberger Forst]
  • A. Ebersberger Forst chosen
    Ebersberger Forst is a large forested area in Upper Bavaria, Germany, known for its extensive woodland, wildlife, and recreational trails near the town of Ebersberg.
  • B. Neckarauer Wald
    Neckarauer Wald is a forested area and local recreational green space in the Mannheim district of Neckarau in southwestern Germany.
  • C. Wermsdorf Forest
    Wermsdorf Forest is a large woodland area in Saxony, Germany, known for its historic hunting grounds and scenic landscapes.
  • D. Habichtswald
    Habichtswald is a low mountain range and forested natural area in central Germany, known for its scenic landscapes and hiking trails near the city of Kassel.
  • E. Schönbuch forest
    Schönbuch forest is a large protected woodland and nature park in Baden-Württemberg, Germany, known for its diverse wildlife, hiking trails, and recreational areas near the city of Stuttgart.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fd1aef888190ba92474af3a49e36 completed April 9, 2026, 1:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d998c6fb4881908a8e13912c405ec8 completed April 11, 2026, 12:41 a.m.
Created at: April 8, 2026, 9:11 p.m.